2024-03-29T12:21:08Zhttps://repositori.uji.es/oai/requestoai:repositori.uji.es:10234/1245032024-03-27T13:06:32Zcom_10234_43662com_10234_9col_10234_43643
Repositori UJI
author
Palazón González, Vicente
author
Marzal Varó, Andrés
author
Vilar Torres, Juan Miguel
2015-06-19T17:46:25Z
2015-06-19T17:46:25Z
2014
0031-3203
http://hdl.handle.net/10234/124503
http://dx.doi.org/10.1016/j.patcog.2014.01.018
Shape descriptions and the corresponding matching techniques must be robust to noise and
invariant to transformations for their use in recognition tasks. Most transformations are relatively
easy to handle when contours are represented by strings. However, starting point invariance is
difficult to achieve. One interesting possibility is the use of cyclic strings, which are strings that
have no starting and final points. We propose new methodologies to use Hidden Markov Models
to classify contours represented by cyclic strings. Experimental results show that our proposals
outperform other methods in the literature.
eng
0031-3203 & 2014 Elsevier Ltd. All rights reserved.
Hidden markov models
cyclic strings
shape recognition
On hidden Markov models and cyclic strings for shape recognition
info:eu-repo/semantics/article
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